I am an AI Researcher with numerous publications including IEEE TNNLS, MICCAI, CBMS, etc. I also have a YouTube channel named "Idiot Developer", where I upload videos related to deep learning. I also write blog posts on my website idiotdeveloper.com. ✅ Projects: 1. Human Face Landmark Detection - using pre-trained MobileNetv2 2. Multiclass Face Segmentation - using UNET. 3. Dog Breed Classification - using pre-trained ResNet50 4. Human Parsing using Crowd Instance-level Human Parsing (CHIP) dataset 5. Brain Tumor Segmentation 6. GAN to generate Anime 7. Retina Blood Vessels 8. Background Removal from Human Images and Videos 9. Implemented various segmentation architectures: U-Net, ResU-Net, DeepLabV3+, DoubleUNet, U2-Net and more. 10. Lung Segmentation 11 Autoencoders

I am a dedicated ML / AI Engineer with over 2 years of experience in Python, Flask, FastAPI, Django, and Generative AI, continuously learning and honing my skills to stay at the cutting edge of technology. As a freelancer, I am committed to delivering high-quality solutions for my clients, bringing a strong foundation in Python development and diverse technical skills to each project. Expertise: • Python Development: Extensive experience in building and deploying applications using Python. • Web Frameworks: Proficient in Flask and FastAPI for developing scalable and efficient web applications. • Deep Learning & Machine Learning Frameworks: Skilled in PyTorch, TensorFlow, and Scikit-Learn for creating and optimizing machine learning models. • Data Science & Visualization: Expertise in Pandas, NumPy, Matplotlib, and OpenCV for data manipulation, analysis, and visualization. • Deployment & DevOps: Hands-on experience with Docker and Anaconda for creating reproducible environments and deploying applications. • Vector Databases: Knowledgeable in Pinecone and ChromaDB for managing and querying high-dimensional data. • Feature Store Management Services: Efficient management of reusable feature sets for robust machine learning pipelines. AI / ML Specializations: • Machine Learning Algorithms: Proficient in SVM, KNN, Regression, Decision Trees, Random Forest, Ensemble methods, and Time Series Analysis. • Deep Learning Architectures: Experience with ANN, CNN, YOLO, LSTMs, RNNs, Transformers and Transfer Learning for various AI applications. • LLM API Integration: Skilled in integrating OpenAI, Gemini, and Claude models using their APIs for production applications, covering prompt engineering, response optimization, rate-limit handling, and performance monitoring. • Generative Models: Proficient in working with diffusion models, GANs, and transformer-based generative architectures for image synthesis, inpainting, and style transfer, with experience in LoRA fine-tuning for model adaptation. • NLP & LLMs: Understanding of NLP tools such as Spacy, NLTK, NER, word2Vec, and TF-IDF; experience with LLMs like Gemini, GPT, Open Source LLMs for advanced language processing tasks. • Text-to-Speech & Speech-to-Text Models: Proficient in developing and fine-tuning speech processing applications, with hands-on experience utilizing Synthflow AI's customizable voice agents and ElevenLabs' advanced multilingual text-to-speech and speech-to-text technologies. • Retrieval-Augmented Generation (RAG): Proficient in integrating retrieval systems with generative models for enhanced AI-driven solutions, including hands-on experience with Multimodal RAG techniques that combine text, images, and audio inputs to improve contextual understanding and response accuracy. Feel free to contact me anytime to discuss how I can contribute to your project. Let's create something great together!

I hold an M.S. in Computer Science from Karazin National University, with a strong foundation in mathematical analysis and linear algebra, which I apply effectively to solve complex challenges in Machine Learning and Computer Vision. With 6 years of extensive commercial experience, I am an AI Engineer with a proven track record of leading development efforts and contributing to all stages of the product lifecycle, aligning technical advancements with business objectives. My expertise covers all major areas of Computer Vision, including image classification, object detection and tracking, image segmentation, and pose estimation. I have delivered impactful, end-to-end solutions in various fields, such as: - Video-driven Sports Game Action Analysis - Satellite Image Processing - AI-powered Smart Parking Systems - Real-time Video Surveillance Systems I specialize in developing custom neural network architectures for Computer Vision applications, leveraging frameworks like TensorFlow, Keras, and PyTorch, as well as tools like OpenCV, MoviePy, and FFmpeg for efficient image and video processing. My programming expertise spans Python and C++, and I have experience building CV-powered web applications using JavaScript. I have successfully contributed to projects in areas such as Sports Analytics, Parking Surveillance Systems, Satellite Image Processing, and Manufacturing & Analytics for the Beauty and Healthcare industries. Proficient in image classification, object detection, action recognition, and more, I leverage advanced neural networks to deliver effective solutions. In addition to my technical skills, I possess a strong foundation in Discrete Mathematics, Statistics, and Differential Equations, with specialized knowledge in digital signal processing, time-series analysis, and unsupervised learning. While working effectively in team environments, I also understand the importance of business logic and strategic goals. I’ve helped businesses and enterprises achieve their goals, drive financial growth, and automate processes to generate significant gains.

I design and deploy production-grade AI systems: from data pipelines to scalable LLM applications. With 7+ years in ML/AI, I specialize in LLM systems, RAG architectures, and MLOps, helping teams move from prototype to reliable, scalable AI in production. My focus is not just building models but ensuring they perform under real-world constraints: latency, cost, hallucination control, and continuous improvement. What I build -End-to-end ML pipelines: ingestion, training, deployment, monitoring -RAG systems with proper evaluation harnesses (retrieval quality, regression catching) -LLM observability: prompt versioning, tracing, feedback loops -Scalable inference (real-time and batch) with GPU optimization -CI/CD for ML with MLflow, Airflow, automated retraining -AI agents with guardrails and reliable tool use Selected results -Fraud detection pipeline (real-time inference) → ~$890K in losses prevented -Forecasting system using ensemble models → 31% accuracy lift over baseline -Multiple LLM products running in production under client SLAs -$3M+ in measurable business impact across deployments (happy to walk through specifics on a call) Stack -Languages/frameworks: Python, FastAPI -LLMs: OpenAI, Anthropic, HuggingFace, LangChain, LlamaIndex -Vector DBs: Pinecone, Weaviate, ChromaDB, FAISS -Infra: AWS, Docker, Supabase, MLflow, Airflow How I work -Replies in 0–4 hours on business days -Production-grade code with tests and docs, not throwaway notebooks -Clear scope, direct communication, focused on business outcomes -Revenue, automation, speed-to-market — that's the scoreboard Let's turn your AI idea into a working product. Send an invite with your project details and I'll get back to you with a clear plan.

Those who build intelligent product features WITHOUT modern development tooling and production-grade backend architecture usually see fragile systems and expensive rewrites. I do it differently. Clients contact me when they face below: • Their LLM feature works but isn’t stable • A RAG pipeline needs proper backend integration • An AI prototype must become production-ready • Performance and scalability issues are emerging • They need a senior engineer who can join an ongoing project and take ownership I specialize in designing and deploying Gen AI systems integrated into clean full-stack architecture. My focus is not experimentation it’s production. Core Specialization • Generative AI application development • Large Language Model (LLM) systems • Retrieval-Augmented Generation (RAG) pipelines • Agentic workflows (LangGraph-based orchestration) • Vector database integration (Pinecone, Weaviate, FAISS) • Structured output validation and evaluation systems • SaaS backend architecture • API-first full-stack engineering • AWS cloud deployment Planning & Product Structuring: • Linear • Framer AI Engineering & Implementation: • Cursor • Claude Code • GitHub Copilot • Replit Backend Architecture & API Layer: • Python • FastAPI • PostgreSQL • Supabase • Firebase • REST APIs • OpenAPI • Async Architecture Frontend & Deployment: • Tailwind CSS • Modern Component Frameworks • Vercel Cloud Infrastructure & Scalability: • AWS (S3, EC2, Lambda, App Runner, Bedrock) • Docker • CI/CD Pipelines • Multi-Tenant SaaS Architecture Monitoring & Production Reliability: • Sentry • Structured Logging • Observability Systems What I Build: • LLM-powered SaaS features • RAG-based knowledge systems • Multi-step agent workflows • Document intelligence and automation tools • AI copilots integrated into existing platforms • Full-stack SaaS platforms with Generative AI layers • Backend restructuring for AI-enabled products I work primarily with funded startups and mid-size product companies. My Typical engagements include: • Joining an active engineering team as senior backend/AI lead • Hardening LLM and RAG systems before scale • Designing full-stack architecture for new AI features • Refactoring unstable AI integrations • Leading backend modernization for SaaS products I’m comfortable stepping into ongoing projects, reviewing codebases, and stabilizing systems quickly. If you’re experimenting with AI concepts, there are many lower-cost options available. If you’re building AI-enabled SaaS features that need to handle real users, real data, and real scale senior architecture matters. I focus on long-term maintainability, measurable performance, and clean engineering. Share your current stack, your AI roadmap, and the bottlenecks you’re facing. I’ll evaluate it and propose a structured approach.

✅ EXPERT-VETTED 🎖 TOP RATED PLUS (Top 1% 🥇 of GLOBAL talent on Upwork). I am a Data Scientist, AI, Machine Learning, and Software Engineer with over 9 years of professional experience building software at any scale. I used to work at large companies such as Yandex as well as in many successful startups. Now I am running Shapeion Technologies, providing software and ML consulting for companies around the globe, to accomplish their business goals. I have been managing startup projects with client teams and have helped draft product roadmaps, planning, and talent acquisition. I have a good network of engineer talent who can help build product MVPs effectively. Products made by me helped startups to raise millions of USD. I have a team of 15 professional Data Annotation specialists who have completed many projects in the Natural Language Processing and Computer Vision fields. They are fluent in the following data annotation platforms: CVAT, Doccano, and ProdiGy. Here is a brief summary of my expertise: ● 2000+ worked hours and 30+ projects completed PERSONALLY only at Upwork ● Created MVPs for various startups and companies that raised millions of USD ● Helped 30+ businesses to reach their goals in time I am proficient in: ✅ Data Science and Machine Learning: ● classification and regression tasks ● time-series prediction (ARIMA, ...) ✅ Natural Language Processing (NLP): ● Text classification (including Sentiment Analysis, Aspect-Based Sentiment Analysis) ● Named Entity Recognition (NER, automatic extraction of relevant entities, like names, locations, dates, etc) ● Chat-Bots (Deep Learning or Rule-Based chat-bots for various domains) Frameworks: SpaCy, HuggingFace, Transformers, NLTK, Langchain, Pinecone Annotation platforms: Doccano, ProdiGy, Clarifai Architectures: BERT, LongFormer, GPT-3, GPT-4 Domains: MedTech, E-Commerce, HRM, AD-tech ✅ Computer Vision (CV): ● Image Classification ● Object Detection (YoLo) ● Instance segmentation / Semantic Segmentation (Mask R-CNN) ● Optical Character Recognition (OCR) Frameworks: PyTorch, TensorFlow, Keras, DarkNet, Detectron, Detectron2, Fast.ai Annotation platforms: CVAT, Clarifai Domains: Medical Imaging, CCTV (surveillance), NFT, LegalTech (document analysis) ✅ Full-Stack Development: ● Backend (FastAPI, Flask, Django, django-rest-framework, Node.js, JavaScript, PHP, Yii Framework) ● Frontend (Vue.js, React.js) ● WordPress ● CI/CD (Docker, docker-compose, Kubernetes, k8s, Ansible, Terraform) ● Databases (PostgreSQL, MySql, MongoDB, OracleDB, ArangoDB, ClickHouse, GraphDB) ● AMQ (Celery, RabbitMQ) Technical skills: Python, Javascript, Go, Java, Spring Boot, Gradle, Node.js, Angular, Tensorflow, Keras, NumPy, Serverless Frameworks, Docker, Terraform, Ansible, Kubernetes, Jenkins, Spinnaker, GitOps, DataOps, AWS. GCP, Azure, JAMstack, GraphQL, MEAN Stack, React, Redux, ES6, Express, MongoDB, Redis, Linux, Etcd, Consul, Kinesis, Redshift, DynamoDB, Spark, Hadoop, Kafka, PostgreSQL, MySQL, ELK, Git, Flask, and Django. Thanks for your consideration! "Alexander was excellent. He managed expectations well and overperformed on the work. Communications were excellent. He saved us 100s of hours of work by automating our processes. He's more expensive than many people on Upwork, but appears to be exceptionally good an reliable." - Tom Mather

I build production-ready AI systems (RAG pipelines, LLM applications, and multilingual NLP) that solve real problems, not just demos that break in production. I'm a PhD researcher in AI/ML with 6+ years building NLP, machine translation, and information retrieval systems, with published work in ACM, Elsevier, EACL, and FIRE. That research background means I can handle the hard problems most freelancers can't: cross-lingual retrieval, low-resource and Indic languages, speech-to-speech systems, and LLM pipelines that actually hold up. What I can build for you: ✔ RAG pipelines and LLM-powered applications (LangChain, HuggingFace, PyTorch) ✔ NLP systems: text classification, NER, sentiment analysis, transformers ✔ Multilingual & cross-lingual AI, with deep expertise in Indic languages ✔ Speech-to-text and speech-to-speech AI ✔ Search and information retrieval engines ✔ Custom ML models: supervised, unsupervised, and deep learning ✔ End-to-end AI pipelines, from prototype to deployment I communicate clearly, hit deadlines, and care about code you can actually maintain. If you have an AI/NLP problem you're not sure is even solvable, that's exactly the kind of project I like. Send me a message and let's scope it.

I'm an expert on machine learning with experience at major investment firms and cancer research. My experience includes, but is not limited to, time series forecasting the stock market and computer vision segmentation models that detect and pinpoint tumors in cancer patients. Technologies I know: - Python, Javascript - Pytorch, Tensorflow, SciKit-Learn, Numpy, Pandas - PostgreSQL, DynamoDB - React, FastAPI, Django, Flask - AWS EC2, AWS Lambda, AWS EKS, AWS S3

Need data extracted from complex websites, AI workflows automated, or an LLM-powered application built? I help startups and businesses automate workflows, extract data at scale, build AI-powered AI applications, and deploy reliable Python systems in production. I focus on delivering real, working systems that save time, reduce manual effort, and scale reliably. ──────────────────────────── What I Can Help You With • Saved hours of manual work through automation • Built production-ready web scraping systems • Developed AI assistants powered by GPT and RAG pipelines • Automated data pipelines processing thousands of records • Delivered reliable APIs used in production environments ──────────────────────────── AI & LLM Engineering OpenAI | Claude | Azure OpenAI | Prompt Engineering | LangChain | RAG | Vector Databases | FAISS | Pinecone | AI Agents | ChatGPT | GPT-4 | OpenAI API | Claude API | CrewAI | AutoGen | MCP (Model Context Protocol) ──────────────────────────── Python Development Python | FastAPI | Django | REST APIs | Automation | API Integration | Backend Development | Web Services Selenium | Playwright | Scrapy | BeautifulSoup | Browser Automation | Web Crawling | Data Extraction ──────────────────────────── Data Engineering ETL | Airflow | Kafka | Pandas | SQL | MongoDB | Data Pipelines | Data Processing ──────────────────────────── Cloud & DevOps AWS | Azure | Docker | CI/CD | RunPod | GPU Cloud | Deployment | Monitoring ──────────────────────────── Core Services ✔ Web Scraping & Data Extraction ✔ Browser Automation ✔ Lead Generation Systems ✔ AI Chatbots & AI Agents ✔ RAG Systems (Retrieval-Augmented Generation) ✔ GPT / LLM Integrations ✔ API Development (FastAPI) ✔ Backend Automation Systems ──────────────────────────── Why Work With Me ✔ Clean, maintainable, production-ready code ✔ Fast communication and clear updates ✔ Scalable systems built for real-world use ✔ Focus on reliability and long-term maintainability ──────────────────────────── Let’s Work Together If you're looking for a Python & AI engineer who can automate workflows, extract complex data, or build production-ready AI systems, feel free to invite me to your project.

I am Younas Khan, a researcher with a Ph.D. in Machine Learning and over 10 years of experience in Machine Learning, Artificial Intelligence, Deep Learning, and Data Science. I have authored papers in Q1 journals and serve as a reviewer for Core A* and A-level conferences in Artificial Intelligence and Machine Learning. I specialize in: * Machine Learning model development, training, validation, and optimization * Research paper writing, editing, structuring, and formatting for journal submission * Systematic Literature Reviews * Thesis and dissertation support * Technical academic writing My Approach: I ensure methodological accuracy, reproducible experiments, and clear scientific communication. Every project is handled with attention to structure, originality, and publication standards. I provide well-documented work and adhere to strict timelines. Services Offered: * ML model design, experimentation, and performance evaluation * End-to-end preparation of publication-ready manuscripts * Development of methodologies, experimental workflows, and result interpretation * Creation of high-quality figures, tables, and visual analytics * Literature synthesis and academic support Research Interests: * Machine Learning * Artificial Intelligence * Deep Learning * Computer Vision * Natural Language Processing * Data Privacy and Security If you need expert support in ML research or publication-ready academic work, I am available to collaborate.